A new diversity estimator

Lukun Zheng () and Jiancheng Jiang ()
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Lukun Zheng: Tennessee Technological University
Jiancheng Jiang: UNC Charlotte

Journal of Statistical Distributions and Applications, 2017, vol. 4, issue 1, 1-13

Abstract: Abstract The maximum likelihood estimator (MLE) of Gini-Simpson’s diversity index (GS) is widely used but suffers from large bias when the number of species is large or infinite. We propose a new estimator of the GS index and show its unbiasedness. Asymptotic normality of the proposed estimator is established when the number of species in the population is finite and known, finite but unknown, and infinite. Simulations demonstrate advantages of our estimator over the MLE, and a real example for the extinction of dinosaurs endorses the use of our approach. Mathematics Subject Classification (MSC) codes is 60E05, which refers to distributions: general theory.

Keywords: Diversity measure; Gini-Simpson’s index; U Statistics (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1186/s40488-017-0063-6

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